In this paper we investigate the word problem of the free Burnside semigroup satisfying x2 = x3 and having two generators. Elements of this semigroup are classes of equivalent words. A natural way to solve the word problem is to select a unique “canonical” representative for each equivalence class. We prove that overlap-free words and socalled almost overlap-free words (this notion is some gene...

We have two polynomial time results for the uniform word problem for a quasivariety Q: (a) The uniform word problem for Q can be solved in polynomial time iff one can find a certain congruence on finite partial algebras in polynomial time. (b) Let Q* be the relational class determined by Q. If any universal Horn class between the universal closure S(Q*) and the weak embedding closure S(Q*) of Q...

A three layer back propagation neural net is set up to determine the dependence between the semantic class of a bisyllabic Chinese word and its two characters. Simulations were performed using a three–layer back–propagation neural net (BPNN) with various combinations of inputs. The inputs are (1) semantic classes of the characters, (2) Entropy of the characters and (3) semantic strengths [1] of...

In a syllable monitoring experiment, Greek and English speakers (N = 20 per language) monitored for [ma] embedded in Greek real and nonce words; [ma] was word-initial, word-medial or word-final, and stressed, unstressed or rhythmically stressed. Both groups spotted stressed [ma] faster than unstressed [ma]; unstressed [ma] was spotted faster by Greek than English participants. Rhythmically stre...

We present a modification of the traditional n-gram language modeling approach that departs from the word-level data representation and seeks to re-express the training text in terms of tokens that could be either words, common phrases or instances of one or several classes. Our iterative optimization algorithm considers alternative parses of the corpus in terms of these tokens, re-estimates to...

Completely data-driven grammar training is prone to over-fitting. Human-defined word class knowledge is useful to address this issue. However, the manual word class taxonomy may be unreliable and irrational for statistical natural language processing, aside from its insufficient linguistic phenomena coverage and domain adaptivity. In this paper, a formalized representation of function word subc...

A novel Ergodic Multigram Hidden Markov Model (HMM) is introduced which models sentence production as a doubly stochastic process, in which word classes are first produced according to a first order Markov model, and then single or multi-character words are generated independently based on the word classes, without word boundary marked on the sentence. This model can be applied to languages wit...

Behavioral (semantic differential) and neural (Evoked Potentials, EPs) responses were related to connotative meaning. The approach was based on Osgood’s semantic analyses and dimensions of Evaluation (E), Potency (P), and Activity (A). The experimental variables were (I) the semantic class of the stimulus word (E+, E, P+ , P-, A+, A-) and (2) the dimension of the semantic scale (E, P. A) which ...

the present study was an attempt to compare the effect of three vlss, namely word-part strategy, word-card strategy and context-clue strategy on immediate and delayed english vocabulary retention of iranian third grade high school students. to this end, 90 students, studying at three high schools in tabriz, in three intact groups, were considered as the participants of the study. in order to en...

This work presents a series of experiments which explore the utility of various acoustic features in the classification of words as prosodically prominent or nonprominent. For this set of experiments, a 35,009 word subset of the Buckeye Speech Corpus was used [12]. This subset is divided across fifty-four segments of the Buckeye Speech Corpus. In a previous study, the words were transcribed for...